Quantification of HER2 and estrogen receptor heterogeneity in breast cancer by single-molecule RNA fluorescence in situ hybridization

Intra-tumor heterogeneity is a pervasive property of human cancers that poses a major clinical challenge. Here, we describe the characterization, at the transcriptional level, of the intra-tumor topography of two prominent breast cancer biomarkers and drug targets, epidermal growth factor receptor 2 (HER2) and estrogen receptor 1 (ER) in 49 archival breast cancer samples. We developed a protocol for single-molecule RNA FISH in formalin-fixed, paraffin-embedded tissue sections (FFPE-smFISH), which enabled us to simultaneously detect and perform absolute quantification of HER2 and ER mature transcripts in single cells and multiple tumor regions. We benchmarked our method with standard diagnostic techniques, demonstrating that FFPE-smFISH is able to correctly classify breast cancers into well-established molecular subgroups. By counting transcripts in thousands of single cells, we identified different expression modes and levels of inter-cellular variability. In samples expressing both HER2 and ER, many cells co-expressed both genes, although expression levels were typically uncorrelated. Finally, we applied diversity metrics from the field of ecology to assess the intra-tumor topography of HER2 and ER gene expression, revealing that the spatial distribution of these key biomarkers can vary substantially even among breast cancers of the same subtype. Our results demonstrate that FFPE-smFISH is a reliable diagnostic assay and a powerful method for quantification of intra-tumor transcriptional heterogeneity of selected biomarkers in clinical samples.

[1]  R. Houtman,et al.  The AF-1-deficient estrogen receptor ERα46 isoform is frequently expressed in human breast tumors , 2016, Breast Cancer Research.

[2]  Christophe Zimmer,et al.  smiFISH and FISH-quant – a flexible single RNA detection approach with super-resolution capability , 2016, Nucleic acids research.

[3]  Hanlee P. Ji,et al.  Pan-cancer analysis of the extent and consequences of intratumor heterogeneity , 2015, Nature Medicine.

[4]  Carlo C. Maley,et al.  An ecological measure of immune-cancer colocalization as a prognostic factor for breast cancer , 2015, Breast Cancer Research.

[5]  Franziska Michor,et al.  In situ single cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2+ breast cancer , 2015, Nature Genetics.

[6]  K. Polyak,et al.  Tumorigenesis: it takes a village , 2015, Nature Reviews Cancer.

[7]  Qingyuan Zhang,et al.  Quantitative assessment of HER2 amplification in HER2-positive breast cancer: its association with clinical outcomes , 2015, Breast Cancer Research and Treatment.

[8]  N. McGranahan,et al.  Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. , 2015, Cancer cell.

[9]  Alexander van Oudenaarden,et al.  Spatially resolved transcriptomics and beyond , 2014, Nature Reviews Genetics.

[10]  C. Botta,et al.  Gene status in HER2 equivocal breast carcinomas: impact of distinct recommendations and contribution of a polymerase chain reaction-based method. , 2014, The oncologist.

[11]  A. Oudenaarden,et al.  Inter- and intratumoral heterogeneity of BCL2 correlates with IgH expression and prognosis in follicular lymphoma , 2014, Blood Cancer Journal.

[12]  Alexander van Oudenaarden,et al.  Genetic and phenotypic diversity in breast tumor metastases. , 2014, Cancer research.

[13]  Robin L. Jones,et al.  Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. , 2014, Cell reports.

[14]  A. van Oudenaarden,et al.  FuseFISH: robust detection of transcribed gene fusions in single cells. , 2013, Cell reports.

[15]  Mats Nilsson,et al.  In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics , 2013, Oncotarget.

[16]  M. Dowsett,et al.  Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[17]  S. Cosimo,et al.  Human epidermal growth factor receptor 2 (HER2)-positive and hormone receptor-positive breast cancer: new insights into molecular interactions and clinical implications. , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.

[18]  C. Perou,et al.  Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013 , 2013, Annals of oncology : official journal of the European Society for Medical Oncology.

[19]  C. Perou,et al.  Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[20]  Sandy L. Klemm,et al.  A versatile genome-scale PCR-based pipeline for high-definition DNA FISH , 2012, Nature Methods.

[21]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[22]  B. Boyan,et al.  Membrane Estrogen Signaling Enhances Tumorigenesis and Metastatic Potential of Breast Cancer Cells via Estrogen Receptor-α36 (ERα36)* , 2012, The Journal of Biological Chemistry.

[23]  J. Troge,et al.  Tumour evolution inferred by single-cell sequencing , 2011, Nature.

[24]  G. Farshid,et al.  Validation of the Multiplex Ligation-dependent Probe Amplification (MLPA) Technique for the Determination of HER2 Gene Amplification in Breast Cancer , 2011, Diagnostic molecular pathology : the American journal of surgical pathology, part B.

[25]  A. Oudenaarden,et al.  Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences , 2008, Cell.

[26]  Scott A. Rifkin,et al.  Imaging individual mRNA molecules using multiple singly labeled probes , 2008, Nature Methods.

[27]  J. Baselga,et al.  The role of hormonal therapy in the management of hormonal-receptor-positive breast cancer with co-expression of HER2 , 2008, Nature Clinical Practice Oncology.

[28]  I. Lossos,et al.  Optimization of RNA Extraction From Formalin-fixed, Paraffin-embedded Lymphoid Tissues , 2007, Diagnostic molecular pathology : the American journal of surgical pathology, part B.

[29]  W. Gerald,et al.  Gene expression profiling in single cells within tissue , 2005, Nature Methods.

[30]  D. Eccles,et al.  Dosage analysis of cancer predisposition genes by multiplex ligation-dependent probe amplification , 2004, British Journal of Cancer.

[31]  D. Zwijnenburg,et al.  Relative quantification of 40 nucleic acid sequences by multiplex ligation-dependent probe amplification. , 2002, Nucleic acids research.

[32]  U. Landegren,et al.  Protein detection using proximity-dependent DNA ligation assays , 2002, Nature Biotechnology.

[33]  F S Fay,et al.  Visualization of single RNA transcripts in situ. , 1998, Science.

[34]  M. Urdea,et al.  An enhanced-sensitivity branched-DNA assay for quantification of human immunodeficiency virus type 1 RNA in plasma , 1996, Journal of clinical microbiology.

[35]  U Landegren,et al.  Padlock probes: circularizing oligonucleotides for localized DNA detection. , 1994, Science.

[36]  C. Metz Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[37]  X. Zhuang,et al.  RNA Imaging with Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH). , 2016, Methods in enzymology.

[38]  A. Wardley,et al.  Re: Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. , 2009, Journal of the National Cancer Institute.